The World Health Organization recommends healthcare workers (HCWs) practice hand hygiene (HH) while providing care. Making alcohol-based hand rub (ABHR) available at points of care is recommended during times of high patient volume, such as the COVID-19 pandemic. In low-and middle-income countries, such as Belize, there may be limited access to HH materials within healthcare facilities (HCF). This paper examines the motivators and barriers to HH among HCWs in the 11 largest public healthcare facilities in Belize and HCWs’ experiences with an intervention. In 2021, focus group discussions (FGDs) gathered HCWs’ HH perceptions and preferences. An intervention was then implemented to increase ABHR access and HH training for HCWs. Post-intervention endpoint FGDs in 2022 documented HCWs’ experiences with interventions. Baseline FGDs revealed that self-protection and protection of one’s household members from illness were key motivators for HCWs’ HH practice. Insufficient time, inadequate access to HH supplies, and gaps in education were barriers to practicing HH. At endpoint, participants appreciated increased access to ABHR and its convenience but did not like ABHR’s effect on hands. Experiences with the training were mixed. To improve HCWs’ HH practices, HH interventions should be tailored to HCWs’ context and learning preferences. © 2024 The Authors.

BACKGROUND: Individual immune responses to SARS-CoV-2 are well-studied, while the combined effect of these responses on population-level immune dynamics remains poorly understood. Given the key role of population immunity on pathogen transmission, delineation of the factors that drive population immune evolution has critical public health implications. METHODS: We enrolled individuals 5 years and older selected using a multistage cluster survey approach in the Northwest and Southeast of the Dominican Republic. Paired blood samples were collected mid-pandemic (Aug 2021) and late pandemic (Nov 2022). We measured serum pan-immunoglobulin antibodies against the SARS-CoV-2 spike protein. Generalized Additive Models (GAMs) and random forest models were used to analyze the relationship between changes in antibody levels and various predictor variables. Principal component analysis and partial dependence plots further explored the relationships between predictors and antibody changes. FINDINGS: We found a transformation in the distribution of antibody levels from an irregular to a normalized single peak Gaussian distribution that was driven by titre-dependent boosting. This led to the convergence of antibody levels around a common immune setpoint, irrespective of baseline titres and vaccination profile. INTERPRETATION: Our results suggest that titre-dependent kinetics driven by widespread transmission direct the evolution of population immunity in a consistent manner. These findings have implications for targeted vaccination strategies and improved modeling of future transmission, providing a preliminary blueprint for understanding population immune dynamics that could guide public health and vaccine policy for SARS-CoV-2 and potentially other pathogens. FUNDING: The study was primarily funded by the Centers for Disease Control and Prevention grant U01GH002238 (EN). Salary support was provided by Wellcome Trust grant 206250/Z/17/Z (AK) and the Australian National Health and Medical Research Council Investigator grant APP1158469 (CLL).

INTRODUCTION: This research aims to characterize disparities in mpox- and vaccine-related knowledge in gay, bisexual, and other men who have sex with men in the U.S. METHODS: The authors conducted a study using the American Men's Internet Survey, which includes 823 cisgender (defined as their gender identity matching their sex assigned at birth) males aged ≥15 years from August 5 to 15, 2022. The authors evaluated sociodemographic and behavioral factors associated with mpox knowledge, including race/ethnicity, region, age group, and HIV pre-exposure prophylaxis use using chi-square tests. RESULTS: The authors identified knowledge gaps, with many participants unsure about whether individuals need 2 doses of the vaccine (34.4%) and whether the vaccine confers immediate protection (27.2%). The authors observed racial and regional disparities (p<0.01), with 24.4% of non-Hispanic Black men and 18.1% of men living in the South reporting little to no mpox awareness. Among the 707 self-reported HIV-negative participants, people who used pre-exposure prophylaxis within the past year were more likely to exhibit high awareness about mpox than people who did not use pre-exposure prophylaxis. CONCLUSIONS: Findings suggest the potential to leverage existing networks (i.e., sexually transmitted infection or general health care services with pre-exposure prophylaxis use) for future targeted health service programming or education campaigns for mpox vaccination among gay, bisexual, and other men who have sex with men.

Many individually randomized group treatment (IRGT) trials randomly assign individuals to study arms but deliver treatments via shared agents, such as therapists, surgeons, or trainers. Post-randomization interactions induce correlations in outcome measures between participants sharing the same agent. Agents can be nested in or crossed with trial arm, and participants may interact with a single agent or with multiple agents. These complications have led to ambiguity in choice of models but there have been no systematic efforts to identify appropriate analytic models for these study designs. To address this gap, we undertook a simulation study to examine the performance of candidate analytic models in the presence of complex clustering arising from multiple membership, single membership, and single agent settings, in both nested and crossed designs and for a continuous outcome. With nested designs, substantial type I error rate inflation was observed when analytic models did not account for multiple membership and when analytic model weights characterizing the association with multiple agents did not match the data generating mechanism. Conversely, analytic models for crossed designs generally maintained nominal type I error rates unless there was notable imbalance in the number of participants that interact with each agent.

PURPOSE: To investigate the prevalence, patterns, and predictors of SARS-CoV-2 RNA and culturable virus in tears of a case-ascertained household cohort. DESIGN: Prospective, longitudinal case-ascertained household cohort identified through convenience sampling. METHODS: This analysis was restricted to individuals who were non-hospitalized, symptomatic, and tested positive for SARS-CoV-2 by nasal RT-PCR. Tears and anterior nasal biospecimens were serially collected throughout the acute period. Tears specimens were collected by the study staff using Schirmer test strips, and nasal specimens were self-collected. For both, SARS-CoV-2 RNA was quantified using qRT-PCR, and culturable virus was detected using presence of cytopathic effect (CPE) in tissue culture; positive CPE was confirmed by a qRT-PCR step. A series of cross-sectional unadjusted analyses were performed investigating the relationship between different sociodemographic determinants and biological factors associated with tears RNA positivity. RESULTS: Among the 83 SARS-CoV-2 infected participants, 10 (12%) had at least one RNA-positive tears specimen. Amongst these 10, 5 (50%) had concurrent presence of culturable virus, at a median of 7 days postsymptom onset (IQR: 4-7 days) (absolute range: 4-8 days). CONCLUSIONS: In this longitudinal cohort, we found evidence of culturable virus in the tears of a small proportion of nonhospitalized SARS-CoV-2 infected individuals. Current public health infection precautions do not account for transmission via tears, so these findings may improve our understanding of potential sources of SARS-CoV-2 transmission and contribute to developing future guidelines.

Despite the emergence of antimicrobial-resistant (AMR) strains of Neisseria gonorrhoeae, the treatment of gonorrhea remains empiric and according to standardized guidelines, which are informed by the national prevalence of resistant strains. Yet, the prevalence of AMR varies substantially across geographic and demographic groups. We investigated whether data from the national surveillance system of AMR gonorrhea in the US could be used to personalize the empiric treatment of gonorrhea. We used data from the Gonococcal Isolate Surveillance Project collected between 2000-2010 to train and validate machine learning models to identify resistance to ciprofloxacin (CIP), one of the recommended first-line antibiotics until 2007. We used these models to personalize empiric treatments based on sexual behavior and geographic location and compared their performance with standardized guidelines, which recommended treatment with CIP, ceftriaxone (CRO), or cefixime (CFX) between 2005-2006, and either CRO or CFX between 2007-2010. Compared with standardized guidelines, the personalized treatments could have replaced 33% of CRO and CFX use with CIP while ensuring that 98% of patients were prescribed effective treatment during 2005-2010. The models maintained their performance over time and across geographic regions. Predictive models trained on data from national surveillance systems of AMR gonorrhea could be used to personalize the empiric treatment of gonorrhea based on patients' basic characteristics at the point of care. This approach could reduce the unnecessary use of newer antibiotics while maintaining the effectiveness of first-line therapy.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2(nd) most accurate model measured by WIS in 2021-22 and the 5(th) most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

School meals play a vital role in supporting student health. Access to school meals was disrupted during COVID-19-related school closures, impacting student nutritional intake and household food insecurity. Data from the National School COVID-19 Prevention Study Survey and school staff focus groups were used to examine challenges to school meal provision in K-12 public schools. Data were analyzed using R and MAXQDA. Survey data indicated that most schools served breakfast and lunch in the cafeteria or classroom during the 2021-2022 school year. City schools were less likely to experience challenges with receiving the foods and supplies needed for school meal programs. Qualitative data revealed that school meal participation increased during the COVID-19 pandemic, however schools encountered challenges when implementing the program including staff shortages and supply chain issues. Findings from this study can help strengthen the K-12 school meal system to equitably serve students in future public health emergencies.

COVID-19, caused by the SARS-CoV-2 virus, is a highly pathogenic emerging infectious disease. Healthcare personnel (HCP) are presumably at higher risk of acquiring emerging infections because of occupational exposure. The prevalence of COVID-19 in HCP is unknown, particularly in low- to middle-income countries like El Salvador. The goal of this study was to determine the seroprevalence of anti-SARS-CoV-2 antibodies among HCP in El Salvador just prior to vaccine rollout in March 2021. We evaluated 2176 participants from a nationally representative sample of national healthcare institutions. We found 40.4% (n = 880) of the study participants were seropositive for anti-spike protein antibodies. Significant factors associated with infection included younger age; living within the central, more populated zone of the country; living in a larger household (≥7 members); household members with COVID-19 or compatible symptoms; and those who worked in auxiliary services (i.e., housekeeping and food services). These findings provide insight into opportunities to mitigate SARS-CoV-2 risk and other emerging respiratory pathogens in HCP in El Salvador.

Public health policy interventions are associated with many important public health achievements. To provide public health practitioners and decision makers with practical approaches for examining and employing evidence-based public health (EBPH) policy interventions, we describe the characteristics and benefits that distinguish EBPH policy interventions from programmatic interventions. These characteristics include focusing on health at a population level, focusing on upstream drivers of health, and involving less individual action than programmatic interventions. The benefits of EBPH policy interventions include more sustained effects on health than many programs and an enhanced ability to address health inequities. Early childhood education and universal preschool provide a case example that illustrates the distinction between EBPH policy and programmatic interventions. This review serves as the foundation for 3 concepts that support the effective use of public health policy interventions: applying core component thinking to understand the population health effects of EBPH policy interventions; understanding the influence of existing policies, policy supports, and the context in which a particular policy is implemented on the effectiveness of that policy; and employing a systems thinking approach to identify leverage points where policy implementation can have a meaningful effect.

PURPOSE: Examine how school-based COVID-19 prevention strategy implementation varied over time, including by local characteristics. METHODS: School administrators (n=335) from a nationally representative sample of K-12 public schools completed four surveys assessing COVID-19 prevention strategies at two-month intervals between October 2021 and June 2022. We calculated weighted prevalence estimates by survey wave. Generalized estimating equations (GEE) were used to model longitudinal changes in strategy implementation, accounting for school and county covariates. RESULTS: Opening doors/windows, daily cleaning, and diagnostic testing were reported by ≥50% of schools at each survey wave. Several strategies were consistently implemented across the 2021-2022 school year (i.e., daily cleaning, opening doors and windows, diagnostic testing) while other strategies increased initially and then declined (i.e., contact tracing, screening testing, on-campus vaccination) or declined consistently throughout the school year (i.e., mask requirement, classroom distancing, quarantine). Although longitudinal changes in strategy implementation did not vary by school characteristics, strategy implementation varied by urban-rural classification and school level throughout the school year. CONCLUSIONS: Strategies that were consistently implemented throughout the school year were also reported by a majority of schools, speaking toward their feasibility for school-based infection control and prevention and potential utility in future public health emergencies.

A growing body of literature uses the concept of core components to better understand small-scale programmatic interventions. Instead of interventions being viewed as unitary "black boxes," interventions are viewed as configurations of core components, which are the parts of interventions that carry their causal potential and therefore need to be reproduced with fidelity to produce the intended effect. To date, the concept of core components has not been as widely applied to public health policy interventions as it has to programmatic interventions. The purpose of this topical review is to familiarize public health practitioners and policy makers with the concept of core components as applied to public health policy interventions. Raising the profile of core component thinking can foster mindful adaptation and implementation of public health policy interventions while encouraging further research to enhance the supporting evidence base. We present 3 types of multilevel interactions in which the core components of a public health policy intervention produce effects at the population level by (1) seeking to directly affect individual behavior, (2) facilitating adoption of programmatic interventions by intermediaries, and (3) encouraging intermediaries to take action that can shape changes in upstream drivers of population health. Changing the unit of analysis from whole policies to core components can provide a basis for understanding how policies work and for facilitating novel evidence-generating strategies and rapid evidence reviews that can inform future adaptation efforts.

Access to water, sanitation, and hygiene (WASH) resources in schools is critical for disease prevention and control, especially during public health emergencies. In Belize, systematic, national data on WASH in schools are needed to inform public health decisions and interventions. From December 2021 to January 2022, a national survey was sent electronically to government and government-aided primary and secondary schools in Belize (N = 308) to gather information on WASH services. From the survey, 12 pilot schools were selected based on the highest self-reported need for WASH resources to participate in additional evaluation and intervention, which included environmental nudges, supplemental supply provision, and hand hygiene education. To understand how the progression of the COVID-19 pandemic may have influenced hand hygiene, facility assessments to evaluate access to hand hygiene resources were conducted in person when most schools reopened for face-to-face learning during the pandemic (March 2022) and 15 months later (June 2023). Among the schools participating in the national survey (N = 221), 55% reported times when water was not available at the schools. Almost 9 in 10 schools (89%) had a functional handwashing station, and 47% reported always having soap for handwashing. Between baseline and follow-up at the 12 pilot schools, we observed decreases in the proportion of functional handwashing access points (-11%), functional handwashing access points accessible for individuals with disabilities (-17%) and small children (-29%), and functional alcohol-based hand rub dispensers (-13%). Despite the ongoing COVID-19 pandemic, we observed gaps in WASH resources in schools in Belize during the onsite assessments at the pilot schools. Schools should be encouraged and provided with WASH resources to maintain vigilance for disease control measures.

Surveillance data can provide rapid, within-season influenza vaccine effectiveness (VE) estimates to guide public health recommendations. Mandatory reporting of influenza vaccine administration to California's immunization information registry began January 1, 2023, and mandatory reporting of all influenza laboratory test results, including negative results, was instituted in California on June 15, 2023. These data, collected by the California Department of Public Health during October 1, 2023-January 31, 2024, were used to calculate interim influenza VE against laboratory-confirmed influenza by comparing the odds of vaccination among case-patients (persons who received a positive influenza laboratory test result) and control patients (those who received a negative influenza laboratory test result). VE was calculated as 1 - adjusted odds ratio using mixed-effects logistic regression, with age, race, and ethnicity as fixed effects and specimen collection week and county as random effects. Overall, during October 1, 2023-January 31, 2024, estimated VE was 45% among persons aged ≥6 months, 56% among children and adolescents aged 6 months-17 years, 48% among adults aged 18-49 years, 36% among those aged 50-64 years, and 30% among those aged ≥65 years. Consistent with some previous influenza seasons, influenza vaccination provided moderate protection against laboratory-confirmed influenza among infants, children, adolescents, and adults. All persons aged ≥6 months without a contraindication to vaccination should receive annual influenza vaccination to reduce influenza illness, severe influenza, and strain on health care resources. Influenza vaccination remains the best way to prevent influenza.

A clear understanding of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.We identified 286 confidence-graded mutations associated with resistance. Compared to phenotypic methods, sensitivity (95% CI) for rifampicin was 90.3% (89.6-90.9%), while for isoniazid it was 78.2% (77.4-79.0%) and their specificities were 96.3% (95.7-96.8%) and 94.4% (93.1-95.5%), respectively. For second-line drugs, sensitivity varied from 67.4% (64.1-70.6%) for capreomycin to 88.2% (85.1-90.9%) for moxifloxacin, with specificity ranging from 90.0% (87.1-92.5%) for moxifloxacin to 99.5% (99.0-99.8%) for amikacin.This study provides a standardised and comprehensive approach for the interpretation of mutations as predictors of M. tuberculosis drug-resistant phenotypes. These data have implications for the clinical interpretation of molecular diagnostics and next-generation sequencing as well as efficient individualised therapy for patients with drug-resistant tuberculosis.

BACKGROUND: Blood is a convenient sample and increasingly used for quantitative gene expression measurements with a variety of diseases including chronic fatigue syndrome (CFS). Quantitative gene expression measurements require normalization of target genes to reference genes that are stable and independent from variables being tested in the experiment. Because there are no genes that are useful for all situations, reference gene selection is an essential step to any quantitative reverse transcription-PCR protocol. Many publications have described appropriate genes for a wide variety of tissues and experimental conditions, however, reference genes that may be suitable for the analysis of CFS, or human blood RNA derived from whole blood as well as isolated peripheral blood mononuclear cells (PBMCs), have not been described. FINDINGS: Literature review and analyses of our unpublished microarray data were used to narrow down the pool of candidate reference genes to six. We assayed whole blood RNA from Tempus tubes and cell preparation tube (CPT)-collected PBMC RNA from 46 subjects, and used the geNorm and NormFinder algorithms to select the most stable reference genes. Phosphoglycerate kinase 1 (PGK1) was one of the optimal normalization genes for both whole blood and PBMC RNA, however, additional genes differed for the two sample types; Ribosomal protein large, P0 (RPLP0) for PBMC RNA and Peptidylprolyl isomerase B (PPIB) for whole blood RNA. We also show that the use of a single reference gene is sufficient for normalization when the most stable candidates are used. CONCLUSIONS: We have identified PGK1 as a stable reference gene for use with whole blood RNA and RNA derived from PBMC. When stable genes are selected it is possible to use a single gene for normalization rather than two or three. Optimal normalization will improve the ability of results from PBMC RNA to be compared with those from whole blood RNA and potentially allows comparison of gene expression results from blood RNA collected and processed by different methods with the intention of biomarker discovery. Results of this study should facilitate large-scale molecular epidemiologic studies using blood RNA as the target of quantitative gene expression measurements.

BACKGROUND: Whole blood is generally processed for plasma and peripheral blood mononuclear cells (PBMCs) from granulocytes/erythrocytes using gradient centrifugation of blood with Histopaue-Ficoll. After separation of plasma and PBMCs, the residual erythrocytes/granulocytes, a rich source of DNA, is often discarded along with the separation medium. In order to isolate DNA from the granulocytes, current methods require the removal of the separation medium and subsequent purification of granulocytes. This report provides a method for extracting DNA using the PAXgene Blood DNA kit from granulocytes without purifying them from the separation medium. FINDINGS: Based on 719 erythrocyte/granulocyte samples stored frozen for approximately 10 years in Ficoll-Hypaque separation medium, the mean yield of DNA was 395 μg (median = 281 μg; range = 1.36 to 2077.2 μg), with mean A260/A280 ratio of 1.84 (median = 1.84; range = 1.17 to 2.23). The quality of isolated DNA was sufficient for use as a template for restriction enzyme digestion, real-time PCR, pyrosequencing, and gel based variable number tandem repeats (VNTR) genotyping. CONCLUSIONS: By demonstrating the extraction of substantial amounts of high quality granulocytes DNA without purifying them from the separation medium, this method offers laboratories and biobanks a flexible and cost-effective approach to obtain plasma, PBMCs, and large amounts of DNA from a single blood collection for a variety of molecular genetics/epidemiologic studies.

Chagas disease is a leading cause of non-ischemic cardiomyopathy in endemic regions of Central and South America. In Belize, Triatoma dimidiata sensu lato has been identified as the predominate taxon but vectorial transmission of Chagas disease is considered to be rare in the country. We recently identified an acute case of vector-borne Chagas disease in the northern region of Belize. Here we present a subsequent investigation of triatomines collected around the case-patient's home. We identified yet undescribed species, closely related to Triatoma huehuetenanguensis vector by molecular systematics methods occurring in the peridomestic environment. The identification of a T. cruzi-positive, novel species of Triatoma in Belize indicates an increased risk of transmission to humans in the region and warrants expanded surveillance and further investigation.

Objective: We sought to characterize patterns of utilization of telemental health among commercially insured individuals over the decade preceding COVID-19. Methods: We developed telemental health service groups from the US PharMetrics Plus database, using diagnostic codes to identify those diagnosed with mental health conditions and procedure codes to capture mental health visits delivered via telehealth sessions. We analyzed 2 indicators of utilization between January 1, 2010, and December 31, 2019: (1) the percentage of patients with mental health needs who used telemental health services and (2) the percentage of all mental health services provided via telehealth. We stratified our analyses by year, patient gender, patient age, and geographic region. Results: The proportion of mental health visits delivered via telemental health increased from 0.002% to 0.162% between 2010 and 2019. A larger proportion of males received telemental health services as compared to females; however, the proportion of mental health visits delivered via telehealth was higher for females than for males. Patients aged 18 to 34 years and those in the western US had the highest utilization compared to other age groups and geographic regions. Conclusions: Telemental health utilization comprised a small fraction of overall mental health services and beneficiaries in the IQVIA PharMetrics Plus claims data, but increased over time, with differences documented in utilization based on patient gender, patient age, geographic region, and type of telemental health claim. Evidence from this study may serve as a pre-pandemic baseline for comparison against future evaluations of telehealth expansion policies.

Due to the emergence of non-vaccine serotypes in vaccinated populations, Streptococcus pneumoniae remains a major global health challenge despite advances in vaccine development. Serotype 16F is among the predominant non-vaccine serotypes identified among vaccinated infants in South Africa (SA). To characterize lineages and antimicrobial resistance in 16F isolates obtained from South Africa and place the local findings in a global context, we analysed 10 923 S. pneumoniae carriage isolates obtained from infants recruited as part of a broader SA birth cohort. We inferred serotype, resistance profile for penicillin, chloramphenicol, cotrimoxazole, erythromycin and tetracycline, and global pneumococcal sequence clusters (GPSCs) from genomic data. To ensure global representation, we also included S. pneumoniae carriage and disease isolates from the Global Pneumococcal Sequencing (GPS) project database (n=19 607, collected from 49 countries across 5 continents, 1995-2018, accessed 17 March 2022). Nine per cent (934/10923) of isolates obtained from infants in the Drakenstein community in SA and 2 %(419/19607) of genomes in the GPS dataset were serotype 16F. Serotype 16F isolates were from 28 different lineages of S. pneumoniae, with GPSC33 and GPSC46 having the highest proportion of serotype 16F isolates at 26 % (346/1353) and 53 % (716/1353), respectively. Serotype 16F isolates were identified globally, but most isolates were collected from Africa. GPSC33 was associated with carriage [OR (95 % CI) 0.24 (0.09-0.66); P=0.003], while GPSC46 was associated with disease [OR (95 % CI) 19.9 (2.56-906.50); P=0.0004]. Ten per cent (37/346) and 15 % (53/346) of isolates within GPSC33 had genes associated with resistance to penicillin and co-trimoxazole, respectively, and 18 % (128/716) of isolates within GPSC46 had genes associated with resistance to co-trimoxazole. Resistant isolates formed genetic clusters, which may suggest emerging resistant lineages. Serotype 16F lineages were common in southern Africa. Some of these lineages were associated with disease and resistance to penicillin and cotrimoxazole. We recommend continuous genomic surveillance to determine the long-term impact of serotype 16F lineages on vaccine efficacy and antimicrobial therapy globally. Investing in vaccine strategies that offer protection over a wide range of serotypes/lineages remains essential. This paper contains data hosted by Microreact.

Potential acute and chronic human health effects associated with exposure to cyanobacteria and cyanotoxins, including respiratory symptoms, are an understudied public health concern. We examined the relationship between estimated cyanobacteria biomass and the frequency of respiratory-related hospital visits for residents living near Green Bay, Lake Michigan, Wisconsin during 2017-2019. Remote sensing data from the Cyanobacteria Assessment Network was used to approximate cyanobacteria exposure through creation of a metric for cyanobacteria chlorophyll-a (Chl(BS)). We obtained counts of hospital visits for asthma, wheezing, and allergic rhinitis from the Wisconsin Hospital Association for ZIP codes within a 3-mile radius of Green Bay. We analyzed weekly counts of hospital visits versus cyanobacteria, which was modelled as a continuous measure (Chl(BS)) or categorized according to World Health Organization's (WHO) alert levels using Poisson generalized linear models. Our data included 2743 individual hospital visits and 114 weeks of satellite derived cyanobacteria biomass indicator data. Peak values of Chl(BS) were observed between the months of June and October. Using the WHO alert levels, 60% of weeks were categorized as no risk, 19% as Vigilance Level, 15% as Alert Level 1, and 6% as Alert Level 2. In Poisson regression models adjusted for temperature, dewpoint, season, and year, there was no association between Chl(BS) and hospital visits (rate ratio [RR] [95% Confidence Interval (CI)] = 0.98 [0.77, 1.24]). There was also no consistent association between WHO alert level and hospital visits when adjusting for covariates (Vigilance Level: RR [95% CI] 0.88 [0.74, 1.05], Alert Level 1: 0.82 [0.67, 0.99], Alert Level 2: 0.98 [0.77, 1.24], compared to the reference no risk category). Our methodology and model provide a template for future studies that assess the association between cyanobacterial blooms and respiratory health.

Listeria monocytogenes can persistently contaminate food processing environments and tolerate sanitizers. Most sequenced strains are from clinical and environmental sources in the contemporary era, with relatively few prior to extensive food processing and sanitizer use. We report the genome sequences of a diverse panel of 83 strains from 1926 to 1964.

To meet the educational needs of students, most schools in the United States (U.S.) reopened for in-person instruction during the 2021-2022 school year implementing a wide range of COVID-19 prevention strategies (e.g., mask requirements). To date, there have been limited studies examining facilitators and barriers to implementing each of the recommended COVID-19 prevention strategies in schools. Twenty-one semistructured interviews were conducted with public school staff from across the U.S. responsible for overseeing prevention strategy implementation. MAXQDA was used for thematic analysis. Findings identified key facilitators including utilizing Centers for Disease Control and Prevention guidance and district policies to guide decision-making at the school level, possessing financial resources to purchase supplies, identifying key staff for implementation, and having school health services infrastructure in place. Key barriers included staff shortages, limited resources, and community opposition. Findings from this study provide important insight into how schools can prepare for future public health emergencies.

BACKGROUND: Pneumoconiosis among coal miners in the USA has been resurgent over the past two decades, despite modern dust controls and regulatory standards. Previously published studies have suggested that respirable crystalline silica (RCS) is a contributor to this disease resurgence. However, evidence has been primarily indirect, in the form of radiographic features. METHODS: We obtained lung tissue specimens and data from the National Coal Workers' Autopsy Study. We evaluated specimens for the presence of progressive massive fibrosis (PMF) and used histopathological classifications to type these specimens into coal-type, mixed-type and silica-type PMF. Rates of each were compared by birth cohort. Logistic regression was used to assess demographic and mining characteristics associated with silica-type PMF. RESULTS: Of 322 cases found to have PMF, study pathologists characterised 138 (43%) as coal-type, 129 (40%) as mixed-type and 55 (17%) as silica-type PMF. Among earlier birth cohorts, coal-type and mixed-type PMF were more common than silica-type PMF, but their rates declined in later birth cohorts. In contrast, the rate of silica-type PMF did not decline in cases from more recent birth cohorts. More recent year of birth was significantly associated with silica-type PMF. CONCLUSIONS: Our findings demonstrate a shift in PMF types among US coal miners, from a predominance of coal- and mixed-type PMF to a more commonly encountered silica-type PMF. These results are further evidence of the prominent role of RCS in the pathogenesis of pneumoconiosis among contemporary US coal miners.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

The global SARS-CoV-2 immune landscape and population protection against emerging variants is largely unknown. We assessed SARS-CoV-2 antibody changes in the Dominican Republic and implications for immunological protection against variants of concern. Between March 2021 and August 2022, 2,300 patients with undifferentiated febrile illnesses were prospectively enrolled. Sera was tested for total anti-spike antibodies and simultaneously collected nasopharyngeal samples for acute SARSCoV-2 infection with RT-PCR. Geometric mean anti-spike titers increased from 6.6 BAU/ml (95% CI 5.1-8.7) to 1,332 BAU/ml (1055-1,682). Multivariable binomial odds ratios for acute SARS-CoV-2 infection were 0.55 (0.40-0.74), 0.38 (0.27-0.55), and 0.27 (0.18-0.40) for the second, third, and fourth versus the first anti-S quartile, with similar findings by viral strain. Integrated serological and virological screening can leverage existing acute fever surveillance platforms to monitor population-level immunological markers and concurrently characterize implications for emergent variant transmission in near real-time. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Monkeypox is a viral zoonotic disease endemic in Central and West Africa. In May 2022, dozens of non-endemic countries reported hundreds of monkeypox cases, most with no epidemiological link to Africa. We identified two lineages of Monkeypox virus (MPXV) among nine 2021 and 2022 U.S. monkeypox cases. A 2021 case was highly similar to the 2022 MPXV outbreak variant, suggesting a common ancestor. Analysis of mutations among these two lineages revealed an extreme preference for GA-to-AA mutations indicative of APOBEC3 cytosine deaminase activity that was shared among West African MPXV since 2017 but absent from Congo Basin lineages. Poxviruses are not thought to be subject to APOBEC3 editing; however, these findings suggest APOBEC3 activity has been recurrent and dominant in recent West African MPXV evolution. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

CONTEXT: Studies comparing initial therapy for multisystem inflammatory syndrome in children (MIS-C) provided conflicting results. OBJECTIVE: To compare outcomes in MIS-C patients treated with intravenous immunoglobulin (IVIG), glucocorticoids, or the combination thereof. DATA SOURCES: Medline, Embase, CENTRAL and WOS, from January 2020 to February 2022. STUDY SELECTION: Randomized or observational comparative studies including MIS-C patients <21 years. DATA EXTRACTION: Two reviewers independently selected studies and obtained individual participant data. The main outcome was cardiovascular dysfunction (CD), defined as left ventricular ejection fraction < 55% or vasopressor requirement ≥ day 2 of initial therapy, analyzed with a propensity score-matched analysis. RESULTS: Of 2635 studies identified, 3 nonrandomized cohorts were included. The meta-analysis included 958 children. IVIG plus glucocorticoids group as compared with IVIG alone had improved CD (odds ratio [OR] 0.62 [0.42-0.91]). Glucocorticoids alone group as compared with IVIG alone did not have improved CD (OR 0.57 [0.31-1.05]). Glucocorticoids alone group as compared with IVIG plus glucocorticoids did not have improved CD (OR 0.67 [0.24-1.86]). Secondary analyses found better outcomes associated with IVIG plus glucocorticoids compared with glucocorticoids alone (fever ≥ day 2, need for secondary therapies) and better outcomes associated with glucocorticoids alone compared with IVIG alone (left ventricular ejection fraction < 55% ≥ day 2). LIMITATIONS: Nonrandomized nature of included studies. CONCLUSIONS: In a meta-analysis of MIS-C patients, IVIG plus glucocorticoids was associated with improved CD compared with IVIG alone. Glucocorticoids alone was not associated with improved CD compared with IVIG alone or IVIG plus glucocorticoids.

BACKGROUND: Research shows associations between bullying victimization and substance use for teens. However, more research about this relationship for younger adolescents and across race/ethnicity is needed. METHODS: Prevalence and pooled logistic regression analyses of 2019 Middle School Youth Risk Behavior Survey data from 13 states (N = 74,059 students) examined associations between self-reported bulling victimization (at school, electronically, and both) and having ever tried cigarette smoking, alcohol, or marijuana; used an electronic vapor product; or misused prescription pain medicine. Regression analyses were adjusted by age and sex/race/ethnicity. RESULTS: All 3 measures of bullying victimization were significantly associated (p < .05) with the 5 substance use behaviors examined (adjusted prevalence ratios ranged from 1.29 to 2.32). These associations held across sexes. Significant associations were found within all 7 race/ethnicity categories, with the most associations reported for the non-Hispanic (NH) white, NH black or African American, Hispanic/Latino, and NH Asian groups. CONCLUSION: The association between bullying and substance use by middle school is a highly relevant issue to consider as students return to classrooms.